Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model

Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model

In order to obtain the pollution condition of transmission line insulators in time, a method of insulator equivalent salt deposit density (ESDD) prediction based on meteorological data is proposed in this paper. The meteorological features that are more closely related to insulator pollution degree...

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Bibliographic Details
Main Authors: Yaoping WANG, Te LI, Kaihua JIANG, Wenhui LI, Qiang WU, Yu WANG
Format: Article
Language:zho
Published: State Grid Energy Research Institute 2023-09-01
Series:Zhongguo dianli
Subjects:
esdd prediction
meteorological characteristics
random forest
extreme learning machine
mind evolution algorithm
adaboost algorithm
Online Access:https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202303084
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https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202303084

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